AI CodeOps

Feature flag

A feature flag turns behaviour on or off at runtime without a new deploy. What flags are used for, the risk of old flags, and the OpenFeature standard.

A feature flag, also called a feature toggle, is a conditional in code whose value can be changed while the software runs, so behaviour changes without a new deploy. OpenFeature describes it, in the simplest case, as an if/else statement that can be controlled at runtime.

What it is

Flags are used for:

  • Release control: merge unfinished work behind a flag that's off, and turn it on when it's ready.
  • Gradual rollout: turn a feature on for a share of users or a group, then widen it.
  • Kill switches: turn off a misbehaving feature in seconds.
  • Experiments: show two versions and compare.

OpenFeature, a Cloud Native Computing Foundation incubating project, defines a vendor-neutral API for evaluating flags. A provider connects that API to a particular flag system, whether open source or commercial.

Why it matters

Flags separate deploying code from releasing a feature, which makes small, frequent merges safer. They also add risk of their own: every flag is a branch in the code that needs testing in both states, and old flags that nobody removes pile up into hidden configuration.

In AI CodeOps

AI CodeOps doesn't manage feature flags. A change behind a flag goes through the same review, approval and release gate as any other change, and the flag itself stays in your own flag system.

Frequently asked questions

Is turning off a flag a rollback?

It undoes the behaviour without a deploy, which is often faster. The code is still there, so a proper fix or removal should follow.

Does AI CodeOps manage feature flags?

No. It doesn't create, evaluate or switch flags, and it doesn't integrate with flag tools today.